BattyLion34 is this running with an agent ?
What's the comparison with a previously working Task (in terms of python packages) ?
GiddyTurkey39 I think I need some more details, what exactly is the scenario here?
Hi @<1547028116780617728:profile|TimelyRabbit96>
You are absolutely correct, we need to allow to override configuration
The code you want to change is here:
None
You can try:
channel = self._ext_grpc.aio.insecure_channel(triton_server_address, options=dict([('grpc.max_send_message_length', 512 * 1024 * 1024), ('grpc.max_receive_message_len...Ohh no I see, yes that makes sense, and I was able to reproduce m thanks!
@<1523701323046850560:profile|OutrageousSheep60> the assumption is that you have "pre_installations.sh" locally (i.e. when you are calling clearml-task ) what will happen is that this bash script will be put on top of the Task and executed before everything else inside the container
does that make sense ?
I assume the task is being launched sequentially. I'm going to prepare a more elaborate example to see what happens.
Let me know if you can produce a mock test, I would love to make sure we support the use case, this is a great example of using pipeline logic 🙂
ReassuredTiger98 I ❤ the DAG in ASCII!!!
port = task_carla_server.get_parameter("General/port")
This looks great! and will acheive exactly what you are after.
BTW: when you are done you can do :task_carla_server.mark_aborted(force=True)And it will shutdown the Clara Task 🙂
Hi SubstantialElk6
noted that clearml-serving does not support Spacy models out of the box and
So this is a good point.
To add any pissing package to the preprocessing docker you can just add them in the following environment variable here: https://github.com/allegroai/clearml-serving/blob/d15bfcade54c7bdd8f3765408adc480d5ceb4b45/docker/docker-compose.yml#L83EXTRA_PYTHON_PACKAGES="spacy>1"
Regrading a custom engine, basically this is supported with --engine custom
you c...
can the ClearML File server be configured to any kind of storage ? Example hdfs or even a database etc..
DeliciousBluewhale87 long story short, no 🙂 the file server, will just store/retrieve/delete files from a local/mounted folder
Is there any ways , we can scale this file server when our data volume explodes. Maybe it wouldnt be an issue in the K8s environment anyways. Or can it also be configured such that all data is stored in the hdfs (which helps with scalablity).I would su...
Hi ColossalDeer61 ,
My question is about existing monitors in the trains-server (preferably the web UI)
So the idea is you run the code once, it creates a Task in the system and verifies the Slack credentials are working. then you can enqueue it in the "services", and voila, you have a monitoring service running, that you can control from the UI and creates alerts to Slack. unfortunately there is no built-in way to achieve that in the UI. but it should not take more than a few minute...
Actually you cannot breakpoint at "atexit" calls (or at least doesn't work with my gdb)
But I would add a few prints here:
https://github.com/allegroai/clearml/blob/aa4e5ea7454e8f15b99bb2c77c4599fac2373c9d/clearml/task.py#L3166
The other order (with custom decorator above pipeline fails - just for you info
)
This is on "purpose" the pipeline decorator has to be the top decorator.
Glad it works!
This looks strange that only a single scalar is reported.
GreasyPenguin14 could you test with the 0.17.5rc4 ?
Also what's the PyCharm / OS?
I do expect it toÂ
pip
 install though which doesn’t root access I think
Correct, it is installed on a venv (exactly for that).
It will not fail if the apt-get fails (only warnings)
Let me know if it worked
Hi @<1636175432829112320:profile|PlainSealion45>
- I used this initial model to create the endpoint with
model add
command.
I think that the initial model needs to be added with model auto-aupdate Not with model add
basically do not call model add - this is static, always using the model ID specified (you can deploy new models with manually callign model add on the same endpoint and specifying diffrent model ID , but again manual)
To Automatically have the m...
I'm guessing the extra index URL can be a URL to the github repo of interest?
The extra index URL is exactly what you would be passing to pip install, meaning it has to comply to pypi artifactory api.
Make sense ?
Hi @<1630377234361487360:profile|RoughSeaturtle43>
code from gitlab repo with ssl cert.
what do you mean by ssl secret? is it SSH or app-token ?
Hi SubstantialElk6ClearML-Data doesn't actually "load" the data, it brings it locally and returns a folder with all your data files, from that point onward, it's up to your code to load it to the framework. Make sense ?
sorry the point where you select the interpreter for pycharm
Oh I see...
Like get the tasks that uses the most metrics API?
Ohh "~/trains.conf" is root probably
Hi GrievingTurkey78
the artifacts are downloaded to the cache folder (and by default the last 100 accessed artifacts are maintained there).
node executes the task all the info will be erased or does this have to be done explicitly?
Are you referring to the trains-agent running a docker?
By default the cache is persistent between execution (i.e. saving time on multiple downloads between experiments)
Hi IrritableGiraffe81
PipelineDecorator.debug_pipeline() runs everything as regular python functions, but "PipelineDecorator.run_locally()" is actually sumulating all the steps on the same local machine (so that it is easier to debug the "real" pipeline running on multiple machines)
What I think is happening is that the casting of the arguments passed to the component fail.
Basically the type hints are currently ignored (we are working on using them for casting in the next version)
but righ...
GreasyPenguin14 whats the clearml version you are using, OS & Python ?
Notice this happens on the "connect_configuration" that seems to be called after the Task was closed, could that be the case ?